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Predictive Search: Is This the Future or the End of Search?

Ever since Google introduced auto-complete in 2004, predictive search has become a welcome part of our internet interactions, helping us search faster, find results quicker, and discover answers to questions we didn’t even know we had.

As predictive search becomes more powerful, tools like Google Now have become capable of delivering relevant, personalized information to users, all but eliminating the need for search as we know it.

Will Google’s continued efforts in predictive search destroy search engines as we know them today? Is Google Now the beginning of a self-destructive path for the king of search?

In this post we’re looking at all aspects of predictive search – how Google uses it in search engines, the role it plays on mobile devices and in new features like Google Now, and what we can expect for predictive search in the future.

The Origins of Google Predictive Search

Google launched the practice of predictive search back in 2004 with Google Suggest, which was then renamed to Google AutoComplete in 2010.

Also in 2010, Google Instant came on the scene, generating search results instantly as users type. While Google Instant and AutoComplete are technically separate features, this partnership, resulting in a more advanced Google predictive search engine experience, is often grouped under the umbrella term of Google Instant.

Google Predictive Search: How Does it Work?

Google’s predictive search feature uses a predictive search algorithm based on popular searches to predict a user’s search query as it is typed, providing a dropdown list of suggestions that changes as the user adds more characters to the search input.

You can see predictive search examples below:

Oh Theon, we are so worried about you!

Google, helping out Pokemon trainers everywhere

This may seem like a minor feat, but people type considerably slower than they read, and Google predictive search saves users quite a bit of time by not making them always have to type their full query.

As Google notes, before Google Instant, a typical search took more than 9 seconds to type in, with some searches taking as long as 30-90 seconds to type (I’m guessing that’s the 60+ crowd). Google says that if Google Instant is used globally, over 3.5 billion seconds will be saved each day from Google predictive search, equating to 11 hours saved every second. Not bad, huh? Now all we need is a machine that stores all those hours saved and uses that stolen time to make us immortal.

In some ways, the necessity of Google Instant shows how pathetic we humans have become. I’ve had times when I don’t even know the name of the device I’m searching for, but as I type my query, Google takes pity on my useless human brain and clues me in to what I’m trying to incoherently articulate. It’s demeaning but really helpful!

Yeah, something like that…

Google Auto Complete is a Pop Culture Icon

Predictive search has become a cornerstone of Google’s identity as a search engine, showcasing their creative efforts to make search easier (and serving as further justification for keeping track of so many users’ queries).

Just run a Google search, click the gear icon in the upper right corner and click “search settings” (NOTE: the gear icon won’t appear until after you’ve run a search).

In search settings you’ll see the option to turn off Google Instant search.

Google Predictive Search: Knowledge Graph

Google’s growing predictive search power gained another foothold with the introduction of its Knowledge Graph in 2013. The Knowledge Graph guesses what type of information a user is searching for when they search a celebrity name or even “museums in Berlin,” and generates specific related content right alongside normal search results.

The Google Knowledge Graph shows that Google isn’t just getting better at predicting users’ questions, but is also getting ever more adept at figuring out what kind of answers users are after.

Google Now Powering Your Life

Google Now embodies the true possibilities of predictive search, serving as a personalized computer assistant that can predict your needs, wants, and deep desires.

For some, Google Now is some strange sorcery, as it delivers important information about the traffic on your morning commute, your updated flight itinerary, and the results of last night’s hockey game on your phone, without you even asking. How did it even know that!?

It’s not magic or mind prediction – the Wizard of Googs is hidden in the Emerald City, behind the curtain, pulling all the strings, smoke, bells, and whistles. In order to provide this relevant info that relates to you and only you, Google uses your private data, accessing (with your permission of course) your Gmail and other info in order to keep tabs on things like flight reservations and hotel bookings.

Google Now has been a group project on Google’s part, combining research and work they’ve done with features like Google Instant, and learning to recognize pop culture references with Knowledge Graph. Google Now is powered by the wealth of search research and Google user services.

Google Now, Apple Later: Apple’s Going After GOKR

Although Google Now is making huge leaps and bounds in predictive search, Apple is always close at the heels – recent rumors claim that Apple may have recently acquired the predictive search app, Gokr. Gokr predictive search uses a kind of knowledge graph that scans and digests info across the web to deliver the appropriate content to users.

Gokr predictive search, combined with Apple’s Siri, could be some serious competition for Google Now.

The Brave New Future of Predictive Search: What’s Next?

With sibling rivalry between Apple and Google for the ultimate virtual personal assistant, we can expect predictive, personal search to become even more popular.

Google Now has been a brilliant move on Google’s part, but one has to wonder if they’re cannibalizing themselves; as predictive search becomes more powerful, the need for classic search engines like Google diminishes. For now, there are still plenty of questions and mysteries we need the Google search engine to answer, but will that always be the case?

Perhaps Google isn’t worried because it sees itself eventually leaving traditional search behind and devoting itself entirely to the final frontier of predictive search.

Google Now is definitely not the end of the line for Google when it comes to predictive search – in fact, we can confidently say it’s only the beginning. With breakthroughs like Google Glass and improved Google voice functionality, it’s hard to say for sure where predictive search fits in.

We can expect to be asked to surrender even more personal data, and with even larger pay-offs. With recent leaks about NSA surveillance, questions about how data should be saved, when and where it should be collected, and how it should be used continue to be major issues.

In our data-driven world, sacrificing privacy has become an acceptable cost for the advantages of technology. Today it’s a peek at our Gmail, tomorrow it’ll be something else, but no matter what is asked of us, Google drives a hard bargain in making our lives easier in exchange – that’s the price of predictive search.

I don't know if I'd consider myself useless because I don't know the name of a product and need to rely on Google to tell me what it is I'm thinking of.Consider Google like that person who comes up with that word you're trying to think of but just can't come up with.I find Google predictive search good for when I misspell a word, give up on my inability to type faster and more accurately than Google can suggest searches, and just click a suggestion.

Thanks for the great article. However, I found it did not really answer the question you used as a title. I actually posted a comment to your article on LinkedIn, however, nobody seems to have noticed, so here it is:What might predictive search mean for SEO? Are suggested search queries actually only based on previous search queries, or is Google also using the Google Books analysis? (Google uses Google Books in order to analyse "natural language" - to determine which words are most often combined with other words. This can and will be used for semantic search.)